Microservices on AWS

Creating Microservices Architectures on AWS

Containers and Microservices to Speed Application Development

As DevOps ideas gain hold, savvy application development teams are looking for the next area of optimization to speed software releases and improve their quality, while reducing maintenance. For many, it’s microservices.

Microservices makes some applications easier to build and maintain – which makes it easier to deliver technology quickly in competitive landscapes.

By breaking applications down into smaller, composable pieces that work together, they can be developed concurrently. That means that individual development groups can choose their preferences, their timelines and process: Group A can develop in Rails and group B can choose Python, requirements for each component may be different and changing. Separation makes it possible to update individual components without having to worry about monolithic code changes.


Faster code delivery, faster time to market
Reduced cost of “failure” supports innovation (fail fast/fail cheap)
Autonomous development teams can do more than just update, they are now free to create new services
New infrastructure provisioning is fast and consistent via automation and self-service

Infrastructure changes that are not automated can be reviewed in the form of CloudFormation template “pull requests”

Flux7 microservices consulting experts design and configure the microservice architecture to enable application development teams to easily move to a service oriented software model.

Our customized solutions include:

Designing and implementing a best practices-based AWS microservice architecture to serve as the foundation
Addressing networking requirements
Leveraging platforms such as AWS’ Lambda or establishing VMs
Configuring Docker containers, auto-scaling, and self-healing Docker clusters
CI/CD of containers setup via Jenkins

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Optimizing Code Delivery Pipelines – Automating development steps reduces time-consuming tasks that slow down the release of software code

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Case Study

A data analytics organization speeds time to market with microservices

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